multivariate data

The basic general purpose program package of multivariate data analysis

微机多元数据分析BASIC语言通用程序包

Multivariate data visualization is an important way of understand multivariate data .

多元数据可视化是理解多元数据的一种重要手段。

Study of Multivariate Data Analysis and Its Application

多变量数据分析及应用研究

Research and Realization of Sharing the National Territory Resource GIS Multivariate Data

国土资源GIS多元数据共享的研究与实现

An Optimization of Feature Selection Based on Graphical Presentation of Multivariate Data

一种基于多元数据图表示的特征选择优化方法

Application of the Multivariate Data Analysis in Agroforestry Experiments with EXCEL

EXCEL在农林试验多因素统计分析中的应用

Complex constellation graph of multivariate data and its optimization method

多元数据的复系数星座图及其优化方法

Statistical Hypotheses Testing Method for Fuzzy Multivariate Data ;

本文给出了一个模糊多元数据的假设检验方法。

Influence Measures of Matrix Statistics in Multivariate Data

多元分析中矩阵统计量的几种影响度量

Hierarchical clustering of multivariate data or distance data ;

聚类多元数据或距离数据；

Further , the multivariate data set often involves missing values inevitably .

此外，多维数据集常不可避免地有丢失值发生。

The multivariate data analysis and the model for extracting remote sensing mineralization and alteration information

多元数据分析与遥感矿化蚀变信息提取模型

Then the relationship between these molecular parameters and the emulsion stability was analyzed by using multivariate data analysis .

在此基础上，采用复合变量分析探讨了减压渣油馏分的各分子参数之间的关系，以及这些分子参数与模拟乳状液稳定性的关系。

Multivariate data processing yielded the characteristic spectra of PbS and its degradation products .

多变量数据分析处理得到PbS及其退化产物的特征光谱。

Evaluation of Agricultural Land Intensive Use based on Multivariate Data : A Case Study of Pinggu District of Beijing

基于多元数据集成的农用地集约利用评价&以北京市平谷区为例

In statistic signal processing and related areas , multivariate data analysis technique has attended wider attention in recent years .

在统计信号处理及其相关领域，多变量数据的描述和分析一直是人们广泛关注的研究课题。

PP goodness-of-fit test for randomly censored multivariate data with the censoring distribution unknown

删截分布未知的多维随机删截数据的PP拟合优度检验

Application of filter - detection and principal component analysis to the study of the multivariate data in lithological - mineralized section

滤波检测与主成分分析技术及其应用

Gauss-Markov model is frequently used in multivariate data analysis and processing , and its parameter estimation is always a hot issue .

Gauss-Markov模型是多元数据分析处理工作中常用的模型，其参数估计与筛选一直是研究的热点。

Independent Component Analysis ( ICA ) is a statistical technique that attempts to decompose multivariate data into many statistically independent components .

独立成分分析（ICA）技术试图将多维数据分解成若干个相互统计独立的分量。

Non-negative matrix factorization ( NMF ) has been proposed for multivariate data analysis , with non-negativity constraints .

非负矩阵因子分解（non-negativeMatrixFactorization，NMF）是对非负数据处理的一种多元统计分析方法。

A subspace graphical representation model of multivariate data is proposed , which unites several traditional multivariate data visualization methods into the same representation framework .

本文提出多元数据的子空间坐标图表示模型，该模型可以将这些传统多元图表示方法统一到同一个表示框架。

The theories and methods of performance evaluation are discussed , the system identification model is introduced into the performance modeling of algorithm systems , and the multivariate data analysis approaches are developed .

论述了性能评估的基本原理和方法，把系统辨识模型引入到算法系统性能的建模中，发展了多元数据分析方法，并探讨了算法性能评价的组织结构和软件支撑环境的保障问题。

The clinical chemistry and multivariate data analysis also showed that the middle and high dose group of sulprostone may have had impacts on the functions and metabolism of kidney .

其次，临床血生化检测和多变量分析结果表明中高剂量硫前列酮对小鼠肾功能和肾脏代谢组也产生了一定程度的影响并引发炎症反应。

However , these targets can not be performed easily especially with the complex multivariate data sets which can be obtained from most of the advanced chemical instruments and chemical plants .

然而，这些目标并不容易实现，特别是当我们处理从先进的化学仪器或化工厂获得的复杂多变量数据集时。

This system software has the function of calculation of in-situ testing results , oil-gas anomaly discrimination , multivariate data analysis , selection of chief indices , and facilitating report preparation etc.

本系统软件具有井中油气化探的现场各种分析测试结果计算、各种油气异常判别、数据多元分析、主要指标选择、辅助报告编写等功能。

Undoubtedly , visualization of the multivariate data set into two-dimensional space is a powerful tool not only to detect the nature clusters but also to extract all the information embedded in this data set .

毫无疑问，将多维数据集降维呈现在二维数据空间，不仅是检测自然聚类也是提取所有数据集内含信息的一个强大的工具。

As a classic multivariate data analysis method , canonical correlation analysis ( CCA ) extracts features through studying the correlation between two groups of variables and has been widely applied in pattern recognition and machine learning recently .

典型相关分析（CCA）作为经典的多元数据分析方法，通过研究两组变量之间的相关关系来进行特征提取，近年来已开始在模式识别和机器学习等多个领域得到广泛的应用。

This paper presents a general fuzzy entropy based-selection criterion for optimal parameters , and the divergence measure of geometrical distribution for multivariate data is defined and its monotonic relation with the classification capability of samples is analyzed .

提出了基于广义模糊熵的特征参数优选准则，定义并分析了高维数据分布中心离散度与样本总体可分性的单调关系。

The basic principle goes like this : taking the multivariate data during the complex production process as input-output information to study , extracting the variables which plays an important role on production result , and then expanding to high-dimension measurement space .

基本原理是：将复杂生产过程的多元数据作为输出一输入信息进行研究，从众多的变量中抽取出对生产结果起重要作用的变量，并依此张成高维测量空间。